import gradio as gr from gradio.mix import Parallel title = 'Comparing different dialogue summarization models' description = 'Here we are going to compare different summarization model namely BART-LARGE model which is trained on samsum data and t5small model which is also trained on the same dataset.' example = [[''' A: Hello B. How are you? B: I'm good. How's your course going on these days? A: It's going well. Pretty tiring but overall fun. B: That's great to hear. If you are free wanna grab a cup of coffee? A: Sure!!!! I recently discovered a new cafe near my home. B: Awesome. Let's go.'''], ['''Rohit: Hi, how’re you? Mahesh: I’m fine. What about you? Rohit: Good. How’s your work going on? Mahesh: Not great. Rohit: Why? What happened? Mahesh: My workplace is far from my home. Most of my time is spent commuting and I'm not able to give time to my family. Rohit: Oh!! That sounds taxing. What are you planning to do now? Mahesh: I will again start applying for jobs near my home. Rohit: Best of luck man!!''']] model1 = gr.Interface.load("huggingface/anegi/t5smallmodel", title = 'BART-Large-cnn-samsum', description = 'This is a pre trained model' ) model2 = gr.Interface.load("huggingface/philschmid/bart-large-cnn-samsum", title = 'T5-small model', description = 'This is a self trained model', ) model3 = gr.Interface.load("huggingface/lidiya/bart-large-xsum-samsum", title = 'T5-small model', description = 'This is a self trained model', ) Parallel(model1, model2 ,model3, title = title, description = description, inputs = gr.inputs.Textbox(lines = 7, label = 'Input Text', placeholder = 'Please enter your dialogue text here'), layout='vertically', examples = example, theme = 'peach' ).launch()